knitr::opts_chunk$set(warning = FALSE, message = FALSE)
pander::panderOptions("table.split.table", Inf)

Load

library(formr)
library(dplyr)
formr_connect(email = credentials$user, password = credentials$password, host = credentials$host)
formr_results("Taeglicher_Fragebogen_1", host = credentials$host, quiet = T) -> diary
## Some items ( choice_of_clothing_2 choice_of_clothing_3 ) were negatively correlated with the total scale and 
## probably should be reversed.  
## To do this, run the function again with the 'check.keys=TRUE' option
formr_items("Taeglicher_Fragebogen_1", host = credentials$host) -> diary_items
# diary = diary %>% select(session, session_id, modified, created, ended, special_events, desirability_partner, NARQ_admiration_1, NARQ_admiration_2, NARQ_admiration_3, NARQ_rivalry_1, NARQ_rivalry_2, NARQ_rivalry_3, NARQ_admiration, NARQ_rivalry)
diary$expired = NA
rm(credentials)
knitr::opts_chunk$set(echo = FALSE)
library(ggplot2)
theme_set(theme_bw())
knitr::opts_chunk$set(error = TRUE)
codebook(diary)

Survey overview

31053 completed rows, 31097 who entered any information, 0 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 31097 rows including unfinished and expired rows.

There were 1204 unique participants, of which 1202 finished filling out at least one survey.

25.83 rows per user code. A repeated survey.

if (repeated_survey) {
    overview = results %>% dplyr::group_by(session) %>% 
        dplyr::summarise(
            n = sum(!is.na(session)),
            expired = sum(!is.na(expired)),
            ended = sum(!is.na(ended))
        ) %>% 
        tidyr::gather(key, value, -session)
    if (length(unique(dplyr::filter(overview, key == "expired")$value)) == 1) {
        overview = dplyr::filter(overview, key != "expired")
    }
    print(
        ggplot2::ggplot(overview, ggplot2::aes(value, ..count..)) + ggplot2::geom_bar() + ggplot2::facet_wrap(~ key, nrow = 1)
    )
}

The first session started on 2014-03-20 17:21:28, the last session on 2016-04-16 22:23:41. People took on average 136.56 minutes (median 3.73) to answer the survey.

high_vals = sum(median(duration$duration) + 4*mad(duration$duration) < duration$duration)
ggplot2::qplot(duration$duration, binwidth = 0.5) + ggplot2::scale_x_continuous(paste("Duration (in minutes), excluding", high_vals, "values above median + 4*MAD"), limits = c(NA, median(duration$duration) + 4*mad(duration$duration)))

Scales

vars = names(results)
for (i in seq_along(vars)) {
    var = vars[i]
    cat(var,"\n", file = "~/Downloads/var.log", append = T)
    scale = results[[ var ]]
    scale_info = attributes(scale)
        if ( !is.null(scale_info)) {
        if (exists("scale", scale_info)) {
        cat(codebook_component_scale( scale, indent ))
        }
    }
}

choice_of_clothing

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  choice_of_clothing  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.61       0.6    0.73      0.16 1.5 0.0031  3.2 0.72
## 
##  lower alpha upper     95% confidence boundaries
## 0.61 0.61 0.62 
## 
##  Reliability if an item is dropped:
##                      raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## choice_of_clothing_1      0.61      0.59    0.74      0.17 1.43   0.0032
## choice_of_clothing_2      0.72      0.72    0.77      0.27 2.59   0.0023
## choice_of_clothing_3      0.70      0.68    0.76      0.23 2.14   0.0022
## choice_of_clothing_4      0.47      0.45    0.62      0.10 0.80   0.0044
## choice_of_clothing_5      0.52      0.49    0.65      0.12 0.98   0.0040
## choice_of_clothing_6      0.51      0.49    0.66      0.12 0.95   0.0040
## choice_of_clothing_7      0.47      0.45    0.61      0.10 0.82   0.0044
## choice_of_clothing_8      0.53      0.51    0.68      0.13 1.03   0.0039
## 
##  Item statistics 
##                          n  raw.r  std.r  r.cor r.drop mean  sd
## choice_of_clothing_1 29982  0.465  0.444  0.275   0.22  3.2 1.5
## choice_of_clothing_2 29978 -0.104 -0.069 -0.260  -0.30  4.5 1.2
## choice_of_clothing_3 29973  0.093  0.113 -0.068  -0.15  3.7 1.4
## choice_of_clothing_4 29970  0.793  0.786  0.815   0.67  3.1 1.4
## choice_of_clothing_5 29971  0.691  0.687  0.665   0.54  2.1 1.3
## choice_of_clothing_6 29969  0.706  0.700  0.654   0.55  3.7 1.4
## choice_of_clothing_7 29967  0.784  0.779  0.817   0.66  2.5 1.4
## choice_of_clothing_8 29968  0.663  0.655  0.597   0.48  2.7 1.4
## 
## Non missing response frequency for each item
##                         1    2    3    4    5    6 miss
## choice_of_clothing_1 0.22 0.11 0.20 0.26 0.15 0.06 0.04
## choice_of_clothing_2 0.02 0.03 0.11 0.31 0.29 0.24 0.04
## choice_of_clothing_3 0.09 0.10 0.20 0.30 0.21 0.10 0.04
## choice_of_clothing_4 0.19 0.14 0.23 0.27 0.13 0.04 0.04
## choice_of_clothing_5 0.49 0.17 0.17 0.11 0.05 0.01 0.04
## choice_of_clothing_6 0.12 0.07 0.16 0.35 0.22 0.08 0.04
## choice_of_clothing_7 0.35 0.17 0.23 0.16 0.07 0.02 0.04
## choice_of_clothing_8 0.29 0.15 0.24 0.20 0.09 0.03 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1130
numeric complete .all 29967
numeric n .all 31097
numeric mean .all 3.203
numeric sd .all 0.7227
numeric min .all 1
numeric median .all 3.25
numeric quantile 25% 2.625
numeric quantile 75% 3.75
numeric max .all 6
numeric hist ▁▂▅▇▇▆▃▁▁▁ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL choice_of_clothing_1 Seriös 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_2 Praktisch 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_3 Sportlich 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_4 Sexy 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_5 Glamourös 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_6 Figurbetont 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_7 Verführerisch 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL choice_of_clothing_8 Auffällig 0 mc-width100 show_value_instead_of_label NULL NULL NULL

NARQ_admiration

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  NARQ_admiration  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean  sd
##       0.87      0.87    0.83      0.68 6.5 0.0014  2.6 1.3
## 
##  lower alpha upper     95% confidence boundaries
## 0.86 0.87 0.87 
## 
##  Reliability if an item is dropped:
##                   raw_alpha std.alpha G6(smc) average_r S/N alpha se
## NARQ_admiration_1      0.78      0.78    0.63      0.63 3.5   0.0025
## NARQ_admiration_2      0.75      0.75    0.60      0.60 3.0   0.0028
## NARQ_admiration_3      0.90      0.90    0.81      0.81 8.8   0.0012
## 
##  Item statistics 
##                       n raw.r std.r r.cor r.drop mean  sd
## NARQ_admiration_1 29963  0.91  0.91  0.86   0.78  2.6 1.5
## NARQ_admiration_2 29963  0.92  0.92  0.88   0.81  2.6 1.5
## NARQ_admiration_3 29963  0.84  0.84  0.68   0.65  2.6 1.5
## 
## Non missing response frequency for each item
##                      1    2    3   4    5    6 miss
## NARQ_admiration_1 0.35 0.14 0.20 0.2 0.08 0.03 0.04
## NARQ_admiration_2 0.36 0.13 0.19 0.2 0.08 0.03 0.04
## NARQ_admiration_3 0.37 0.13 0.19 0.2 0.08 0.03 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1134
numeric complete .all 29963
numeric n .all 31097
numeric mean .all 2.59
numeric sd .all 1.316
numeric min .all 1
numeric median .all 2.667
numeric quantile 25% 1.333
numeric quantile 75% 3.667
numeric max .all 6
numeric hist ▇▃▂▅▂▅▁▂▁▁ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL NARQ_admiration_1 …hatte ich das Gefühl es verdient zu haben, als große Persönlichkeit angesehen zu werden. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL NARQ_admiration_2 … habe ich viel Kraft daraus gezogen, eine ganz besondere Person zu sein. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL NARQ_admiration_3 … habe ich es geschafft, mit meinen besonderen Beiträgen im Mittelpunkt zu stehen. 0 mc-width100 show_value_instead_of_label NULL NULL NULL

NARQ_rivalry

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  NARQ_rivalry  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.76      0.76     0.7      0.51 3.2 0.0022  1.3 0.69
## 
##  lower alpha upper     95% confidence boundaries
## 0.76 0.76 0.77 
## 
##  Reliability if an item is dropped:
##                raw_alpha std.alpha G6(smc) average_r S/N alpha se
## NARQ_rivalry_1      0.64      0.65    0.48      0.48 1.8   0.0040
## NARQ_rivalry_2      0.56      0.57    0.39      0.39 1.3   0.0049
## NARQ_rivalry_3      0.80      0.80    0.67      0.67 4.0   0.0023
## 
##  Item statistics 
##                    n raw.r std.r r.cor r.drop mean   sd
## NARQ_rivalry_1 29962  0.85  0.84  0.73   0.63  1.3 0.88
## NARQ_rivalry_2 29963  0.89  0.87  0.80   0.70  1.3 0.90
## NARQ_rivalry_3 29962  0.72  0.76  0.54   0.48  1.2 0.72
## 
## Non missing response frequency for each item
##                   1    2    3    4    5    6 miss
## NARQ_rivalry_1 0.82 0.08 0.05 0.03 0.01 0.01 0.04
## NARQ_rivalry_2 0.86 0.06 0.03 0.03 0.01 0.01 0.04
## NARQ_rivalry_3 0.87 0.06 0.03 0.02 0.01 0.00 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1135
numeric complete .all 29962
numeric n .all 31097
numeric mean .all 1.296
numeric sd .all 0.6882
numeric min .all 1
numeric median .all 1
numeric quantile 25% 1
numeric quantile 75% 1
numeric max .all 6
numeric hist ▇▁▁▁▁▁▁▁▁▁ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL NARQ_rivalry_1 … habe ich genervt reagiert, wenn eine andere Frau mir die Schau gestohlen hat. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL NARQ_rivalry_2 … wollte ich, dass meine Konkurrentinnen sich blamieren oder ignoriert werden. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL NARQ_rivalry_3 … hatte ich das Gefühl, dass die meisten Frauen ziemliche Versagerinnen sind. 0 mc-width100 show_value_instead_of_label NULL NULL NULL

male_jealousy

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  male_jealousy  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean   sd
##       0.54      0.56    0.46       0.3 1.3 0.0043  1.3 0.64
## 
##  lower alpha upper     95% confidence boundaries
## 0.54 0.54 0.55 
## 
##  Reliability if an item is dropped:
##                 raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## male_jealousy_1      0.38      0.40    0.25      0.25 0.66   0.0066
## male_jealousy_2      0.48      0.50    0.33      0.33 1.00   0.0055
## male_jealousy_3      0.47      0.47    0.30      0.30 0.88   0.0060
## 
##  Item statistics 
##                     n raw.r std.r r.cor r.drop mean   sd
## male_jealousy_1 29962  0.78  0.75  0.54   0.40  1.4 0.96
## male_jealousy_2 29963  0.75  0.71  0.45   0.34  1.4 0.98
## male_jealousy_3 29962  0.65  0.72  0.48   0.36  1.2 0.68
## 
## Non missing response frequency for each item
##                    1    2    3    4    5    6 miss
## male_jealousy_1 0.82 0.07 0.05 0.04 0.01 0.01 0.04
## male_jealousy_2 0.83 0.06 0.04 0.04 0.01 0.01 0.04
## male_jealousy_3 0.92 0.04 0.02 0.01 0.01 0.01 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1135
numeric complete .all 29962
numeric n .all 31097
numeric mean .all 1.315
numeric sd .all 0.6392
numeric min .all 1
numeric median .all 1
numeric quantile 25% 1
numeric quantile 75% 1.333
numeric max .all 6
numeric hist ▇▁▁▁▁▁▁▁▁▁ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL male_jealousy_1 … hat mich mein Partner eifersüchtig gemacht. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL male_jealousy_2 … hat mein Partner auf meinen Umgang mit anderen Männern eifersüchtig reagiert. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL male_jealousy_3 … hat mir mein Partner erzählt, er habe Komplimente von anderen Frauen erhalten. 0 mc-width100 show_value_instead_of_label NULL NULL NULL

male_mate_retention

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  male_mate_retention  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r  S/N    ase mean  sd
##       0.31      0.31    0.18      0.18 0.45 0.0078  3.2 1.5
## 
##  lower alpha upper     95% confidence boundaries
## 0.29 0.31 0.32 
## 
##  Reliability if an item is dropped:
##                       raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## male_mate_retention_1     0.184      0.18   0.034      0.18   NA       NA
## male_mate_retention_2     0.034      0.18      NA        NA 0.18   0.0024
## 
##  Item statistics 
##                           n raw.r std.r r.cor r.drop mean  sd
## male_mate_retention_1 29962  0.73  0.77  0.33   0.18  2.3 1.8
## male_mate_retention_2 29962  0.81  0.77  0.33   0.18  4.0 2.1
## 
## Non missing response frequency for each item
##                          1    2    3    4    5   6 miss
## male_mate_retention_1 0.59 0.06 0.07 0.12 0.07 0.1 0.04
## male_mate_retention_2 0.25 0.04 0.07 0.12 0.12 0.4 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1135
numeric complete .all 29962
numeric n .all 31097
numeric mean .all 3.158
numeric sd .all 1.483
numeric min .all 1
numeric median .all 3.5
numeric quantile 25% 2
numeric quantile 75% 4
numeric max .all 6
numeric hist ▇▂▃▃▇▂▂▂▁▂ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL male_mate_retention_1 … hat mich mein Partner gefragt, mit wem ich den Tag verbracht habe. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL male_mate_retention_2 … hat mir mein Partner gesagt, dass er mich liebt. 0 mc-width100 show_value_instead_of_label NULL NULL NULL

attention

Reliability

psych::print.psych(scale_info$reliability)
## 
## Reliability analysis  attention  
## Call: psych::alpha(x = results[, scale_item_names], title = save_scale, 
##     check.keys = FALSE)
## 
##   raw_alpha std.alpha G6(smc) average_r S/N    ase mean  sd
##       0.74      0.75    0.59      0.59 2.9 0.0029  3.8 1.5
## 
##  lower alpha upper     95% confidence boundaries
## 0.74 0.74 0.75 
## 
##  Reliability if an item is dropped:
##             raw_alpha std.alpha G6(smc) average_r  S/N alpha se
## attention_1      0.59      0.59    0.35      0.59   NA       NA
## attention_2      0.35      0.59      NA        NA 0.59   0.0044
## 
##  Item statistics 
##                 n raw.r std.r r.cor r.drop mean  sd
## attention_1 29960  0.88  0.89  0.69   0.59  4.3 1.5
## attention_2 29960  0.91  0.89  0.69   0.59  3.3 1.8
## 
## Non missing response frequency for each item
##                1    2    3    4    5    6 miss
## attention_1 0.10 0.05 0.10 0.26 0.24 0.25 0.04
## attention_2 0.26 0.11 0.17 0.18 0.14 0.14 0.04

Likert plot

old_height = knitr::opts_chunk$get("fig.height")
new_height = ncol(attributes(scale)$likert_plot$items)
new_height = ifelse(new_height > 20, 20, new_height)
knitr::opts_chunk$set(fig.height = new_height)
likert:::plot.likert(scale_info$likert_plot)

knitr::opts_chunk$set(fig.height = old_height)

Distribution

binwidth = mean(diff(sort(unique(scale))))
choices = scale_info$item[[1]]$choices
old_width = knitr::opts_chunk$get("fig.width")
if (!is.null(choices)) {
    new_width = 1.5 * length(choices)
    new_width = ifelse(new_width > 20, 20, new_width)
    knitr::opts_chunk$set(fig.width = new_width)
}
dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = scale)) +
    ggplot2::stat_bin(binwidth = binwidth) + 
    ggplot2::ggtitle(scale_name, subtitle = paste("aggregated over", length(scale_info$item), "items")) + 
    ggplot2::xlab("Choices") + 
    ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))

dist_plot

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(scale))
type stat level value
numeric missing .all 1137
numeric complete .all 29960
numeric n .all 31097
numeric mean .all 3.756
numeric sd .all 1.474
numeric min .all 1
numeric median .all 4
numeric quantile 25% 2.5
numeric quantile 75% 5
numeric max .all 6
numeric hist ▇▃▆▆▇▇▇▇▅▇ 0

Items

pander::pander(dplyr::bind_rows(
    lapply(scale_info$item, function(x) { 
        x$label_parsed = x$choices = x$choice_list = x$study_id = x$id = NULL
        as.data.frame(t(x)) })
))
type type_options name label optional class showif value order
mc_button NULL attention_1 … habe ich meinem Partner gezeigt, dass er mir wichtig ist. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
mc_button NULL attention_2 … habe ich meinem Partner gezeigt, dass ich mich von ihm sexuell angezogen fühle. 0 mc-width100 show_value_instead_of_label NULL NULL NULL

Single items

for (i in seq_along(vars)) {
    var = vars[i]
    cat(var,"\n", file = "~/Downloads/var.log", append = TRUE)
    item = results[[ var ]]
    item_info = attributes(item)
    if ( !is.null(item_info)) {
        if (exists("part_of_scale", item_info) || exists("scale", item_info)) {
            next
        } else if (exists("item", item_info)) {
            cat(codebook_component_single_item( item, indent ))
        } else {
            cat(codebook_component_fallback( item, var, indent))
        }
    }
}

modified

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
POSIXct missing .all 0
POSIXct complete .all 31097
POSIXct n .all 31097
POSIXct min .all 1395332635
POSIXct max .all 1466869368
POSIXct median .all 1404748079
POSIXct n_unique .all 30963

Attributes

pander::pander(item_info)
  • class: POSIXct and POSIXt
  • tzone:
  • label: user last edited survey

created

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
POSIXct missing .all 0
POSIXct complete .all 31097
POSIXct n .all 31097
POSIXct min .all 1395332488
POSIXct max .all 1460838221
POSIXct median .all 1404747737
POSIXct n_unique .all 30956

Attributes

pander::pander(item_info)
  • class: POSIXct and POSIXt
  • tzone:
  • label: user first opened survey

ended

Distribution

dist_plot = ggplot2::ggplot() +
    ggplot2::geom_bar(ggplot2::aes(x = item)) +
    ggplot2::stat_bin() + 
    ggplot2::ggtitle(item_name, subtitle = item_label) + 
    ggplot2::xlab("Choices")

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
POSIXct missing .all 44
POSIXct complete .all 31053
POSIXct n .all 31097
POSIXct min .all 1395332636
POSIXct max .all 1466869452
POSIXct median .all 1404679062
POSIXct n_unique .all 30688

Attributes

pander::pander(item_info)
  • class: POSIXct and POSIXt
  • tzone:
  • label: user finished survey

communication_partner_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 2.542
integer sd .all 0.5638
integer min .all 1
integer median .all 3
integer quantile 25% 2
integer quantile 75% 3
integer max .all 3
integer hist ▁▁▁▁▆▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL communication_partner_1 Wie oft haben Sie seit Ihrem letzten Eintrag mit Ihrem Partner kommuniziert? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Gar nicht
  • 2: Wenig
  • 3: Viel

communication_partner_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 2171
integer complete .all 28926
integer n .all 31097
integer mean .all 1.92
integer sd .all 1.49
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 2
integer max .all 7
integer hist ▇▂▁▁▂▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL communication_partner_2 Auf welche Art haben Sie hauptsächlich mit Ihrem Partner kommuniziert? 0 NULL current(communication_partner_1) == 2 || current(communication_partner_1) == 3 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Direkter persönlicher Kontakt
  • 2: Telefon
  • 3: SMS
  • 4: mobile Nachrichtenapp (z.B. Whatsapp)
  • 5: Webcam (z.B. Skype)
  • 6: Email
  • 7: Chat (z.B. Facebook)

mate_retention_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 1.452
integer sd .all 0.4977
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 2
integer max .all 2
integer hist ▇▁▁▁▁▁▁▁▁▆ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL mate_retention_1 Haben Sie die letzte Nacht mit Ihrem Partner verbracht? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja
  • 2: nein

relationship_satisfaction_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 4.839
integer sd .all 1.208
integer min .all 1
integer median .all 5
integer quantile 25% 4
integer quantile 75% 6
integer max .all 6
integer hist ▁▁▁▂▁▅▁▇▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL relationship_satisfaction_1 Wie zufrieden waren Sie insgesamt seit Ihrem letzten Eintrag mit Ihrer Beziehung? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Nicht zufrieden
  • 2: Überwiegend nicht zufrieden
  • 3: Eher nicht zufrieden
  • 4: Eher zufrieden
  • 5: Überwiegend zufrieden
  • 6: Sehr zufrieden

mate_retention_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 2.441
integer sd .all 0.6548
integer min .all 1
integer median .all 3
integer quantile 25% 2
integer quantile 75% 3
integer max .all 3
integer hist ▂▁▁▁▆▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL mate_retention_2 Haben Sie seit Ihrem letzten Eintrag öffentlich Intimitäten (z.B. Händchenhalten, Küssen, in den Arm nehmen) ausgetauscht? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja (1x)
  • 2: ja (mehrfach)
  • 3: nein

sexual_intercourse_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 3.108
integer sd .all 1.218
integer min .all 1
integer median .all 3
integer quantile 25% 2
integer quantile 75% 4
integer max .all 5
integer hist ▃▁▅▁▇▁▁▆▁▃ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL sexual_intercourse_1 Wie sehr hatten Sie seit Ihrem letzten Eintrag Lust, mit Ihrem Partner Geschlechtsverkehr zu haben? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: gar nicht
  • 2: kaum
  • 3: etwas
  • 4: viel
  • 5: sehr viel

sexual_intercourse_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1109
integer complete .all 29988
integer n .all 31097
integer mean .all 2.632
integer sd .all 0.7301
integer min .all 1
integer median .all 3
integer quantile 25% 3
integer quantile 75% 3
integer max .all 3
integer hist ▂▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL sexual_intercourse_2 Hatten Sie seit Ihrem letzten Eintrag mit Ihrem Partner Geschlechtsverkehr? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja (1x)
  • 2: ja (mehrfach)
  • 3: nein

sexual_intercourse_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 24561
integer complete .all 6536
integer n .all 31097
integer mean .all 1.603
integer sd .all 0.4892
integer min .all 1
integer median .all 2
integer quantile 25% 1
integer quantile 75% 2
integer max .all 2
integer hist ▅▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL sexual_intercourse_3 Wer hat den Geschlechtsverkehr stärker initiiert? 0 NULL current(sexual_intercourse_2) == 1 || current(sexual_intercourse_2) == 2 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ich
  • 2: mein Partner

sexual_intercourse_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 24562
integer complete .all 6535
integer n .all 31097
integer mean .all 5.136
integer sd .all 0.9874
integer min .all 1
integer median .all 5
integer quantile 25% 5
integer quantile 75% 6
integer max .all 6
integer hist ▁▁▁▁▁▃▁▆▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL sexual_intercourse_4 Wie zufrieden waren Sie mit dem Geschlechtsverkehr? 0 NULL current(sexual_intercourse_2) == 1 || current(sexual_intercourse_2) == 2 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Nicht zufrieden
  • 2: Überwiegend nicht zufrieden
  • 3: Eher nicht zufrieden
  • 4: Eher zufrieden
  • 5: Überwiegend zufrieden
  • 6: Sehr zufrieden

sexual_intercourse_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1110
integer complete .all 29987
integer n .all 31097
integer mean .all 2.684
integer sd .all 0.6787
integer min .all 1
integer median .all 3
integer quantile 25% 3
integer quantile 75% 3
integer max .all 3
integer hist ▁▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL sexual_intercourse_5 Hatten Sie seit Ihrem letzten Eintrag anderen sexuellen Kontakt mit Ihrem Partner (Oralverkehr, Petting etc.)? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja (1x)
  • 2: ja (mehrfach)
  • 3: nein

extra_pair_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1110
integer complete .all 29987
integer n .all 31097
integer mean .all 1.986
integer sd .all 0.1159
integer min .all 1
integer median .all 2
integer quantile 25% 2
integer quantile 75% 2
integer max .all 2
integer hist ▁▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL extra_pair_1 Hatten Sie seit Ihrem letzten Eintrag intimen Kontakt mit einer anderen Person als Ihrem Partner? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja
  • 2: nein

extra_pair_1b

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 30690
integer complete .all 407
integer n .all 31097
integer mean .all 1.661
integer sd .all 0.474
integer min .all 1
integer median .all 2
integer quantile 25% 1
integer quantile 75% 2
integer max .all 2
integer hist ▅▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL extra_pair_1b Hatten Sie seit Ihrem letzten Eintrag Sex mit einer anderen Person als Ihrem Partner? 0 NULL current(extra_pair_1) == 1 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja
  • 2: nein

menstruation_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1110
integer complete .all 29987
integer n .all 31097
integer mean .all 1.839
integer sd .all 0.3673
integer min .all 1
integer median .all 2
integer quantile 25% 2
integer quantile 75% 2
integer max .all 2
integer hist ▂▁▁▁▁▁▁▁▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL menstruation_1 Hatten Sie seit Ihrem letzten Eintrag menstruelle Blutungen (Ihre Periode)? 0 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja
  • 2: nein

menstruation_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 26288
integer complete .all 4809
integer n .all 31097
integer mean .all 3.43
integer sd .all 1.682
integer min .all 1
integer median .all 3
integer quantile 25% 2
integer quantile 75% 5
integer max .all 6
integer hist ▇▇▁▇▁▇▁▇▁▆ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc NULL menstruation_2 War heute der erste Tag Ihrer menstruellen Blutung (Periode)? 0 mc_vertical current(menstruation_1) == 1 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: ja
  • 2: nein (gestern)
  • 3: nein (vorgestern)
  • 4: nein (vor 3 Tagen)
  • 5: nein (vor 4 Tagen)
  • 6: nein (Beginn liegt noch länger zurück)

menstruation_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 26288
integer complete .all 4809
integer n .all 31097
integer mean .all 1.572
integer sd .all 0.717
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 2
integer max .all 3
integer hist ▇▁▁▁▅▁▁▁▁▂ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL menstruation_3 Wie stark ist Ihre menstruelle Blutung (Periode) heute? 0 NULL current(menstruation_1) == 1 NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1:
  • 2:
  • 3:

self_esteem_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1130
integer complete .all 29967
integer n .all 31097
integer mean .all 4.276
integer sd .all 1.19
integer min .all 1
integer median .all 4
integer quantile 25% 4
integer quantile 75% 5
integer max .all 6
integer hist ▁▁▁▃▁▇▁▇▁▃ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL self_esteem_1 … war ich im Großen und Ganzen zufrieden mit mir selbst. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

desirability_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1130
integer complete .all 29967
integer n .all 31097
integer mean .all 3.676
integer sd .all 1.413
integer min .all 1
integer median .all 4
integer quantile 25% 3
integer quantile 75% 5
integer max .all 6
integer hist ▃▂▁▅▁▇▁▅▁▂ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL desirability_1 … habe ich mich sexuell begehrenswert gefühlt. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

desirability_partner

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1132
integer complete .all 29965
integer n .all 31097
integer mean .all 3.818
integer sd .all 1.453
integer min .all 1
integer median .all 4
integer quantile 25% 3
integer quantile 75% 5
integer max .all 6
integer hist ▃▂▁▅▁▇▁▆▁▃ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL desirability_partner …fand ich meinen Partner besonders sexuell anziehend. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

jealousy_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1134
integer complete .all 29963
integer n .all 31097
integer mean .all 2.406
integer sd .all 1.825
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▁▁▁▁▂▁▁▁▂ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL jealousy_1 … habe ich meinen Partner gefragt, mit wem er den Tag verbracht hat. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

mate_retention_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1135
integer complete .all 29962
integer n .all 31097
integer mean .all 2.869
integer sd .all 1.703
integer min .all 1
integer median .all 3
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▂▁▃▁▅▁▃▁▂ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL mate_retention_3 … habe ich mich für meinen Partner besonders hübsch gemacht. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

mate_retention_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1135
integer complete .all 29962
integer n .all 31097
integer mean .all 3.991
integer sd .all 2.054
integer min .all 1
integer median .all 5
integer quantile 25% 1
integer quantile 75% 6
integer max .all 6
integer hist ▅▁▁▂▁▂▁▂▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL mate_retention_4 … habe ich meinem Partner gesagt, dass ich ihn liebe. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

mate_retention_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1135
integer complete .all 29962
integer n .all 31097
integer mean .all 1.623
integer sd .all 1.227
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 2
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL mate_retention_5 … habe ich vor meinem Partner über andere Frauen gelästert. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

mate_retention_6

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1136
integer complete .all 29961
integer n .all 31097
integer mean .all 2.784
integer sd .all 1.568
integer min .all 1
integer median .all 3
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▃▁▅▁▅▁▂▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL mate_retention_6 … war ich in Bezug auf meinen Partner sehr anhänglich. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

male_attention_1

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1137
integer complete .all 29960
integer n .all 31097
integer mean .all 3.541
integer sd .all 1.842
integer min .all 1
integer median .all 4
integer quantile 25% 2
integer quantile 75% 5
integer max .all 6
integer hist ▇▃▁▅▁▆▁▆▁▇ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL male_attention_1 … hat mir mein Partner gezeigt, dass er sich von mir sexuell angezogen fühlt. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_2

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1137
integer complete .all 29960
integer n .all 31097
integer mean .all 2.604
integer sd .all 1.608
integer min .all 1
integer median .all 2
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▂▁▃▁▃▁▂▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_2 …war es mir wichtig, dass mich andere Männer als attraktiv wahrnehmen. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_3

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.954
integer sd .all 1.514
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 3
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_3 … habe ich Komplimente von anderen Männern erhalten. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_4

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.295
integer sd .all 0.9242
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_4 … habe ich via Medien mit Freunden, Bekannten oder Kollegen geflirtet. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_5

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.94
integer sd .all 1.719
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 2
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_5 … bin ich ohne meinen Partner ausgegangen. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_6

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 2.254
integer sd .all 1.843
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▂ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_6 … bin ich ohne meinen Partner an einen Ort gegangen, wo man Männer treffen kann. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_7

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.595
integer sd .all 1.241
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_7 … habe ich mir Gedanken über einen anderen potentiellen Partner gemacht. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_8

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.248
integer sd .all 0.8024
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_8 … habe ich mit Männern geflirtet, die ich nicht kannte. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_9

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.39
integer sd .all 1.053
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_9 … habe ich mit Freunden, Kollegen oder Bekannten geflirtet. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_10

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.518
integer sd .all 1.216
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_10 … habe ich mich zu einem Freund, Bekannten oder Kollegen hingezogen gefühlt 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_11

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.237
integer sd .all 0.801
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_11 … habe ich mich zu einem Mann hingezogen gefühlt, den ich nicht kannte. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_12

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 2.248
integer sd .all 1.629
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 4
integer max .all 6
integer hist ▇▁▁▁▁▂▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_12 … sind mir attraktive Männer in meiner Umgebung aufgefallen. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

extra_pair_13

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}

knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
integer missing .all 1138
integer complete .all 29959
integer n .all 31097
integer mean .all 1.481
integer sd .all 1.2
integer min .all 1
integer median .all 1
integer quantile 25% 1
integer quantile 75% 1
integer max .all 6
integer hist ▇▁▁▁▁▁▁▁▁▁ 0

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
mc_button NULL extra_pair_13 … hatte ich sexuelle Fantasien mit anderen Männern als meinem Partner. 0 mc-width100 show_value_instead_of_label NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}
  • 1: Stimme nicht zu
  • 2: Stimme überwiegend nicht zu
  • 3: Stimme eher nicht zu
  • 4: Stimme eher zu
  • 5: Stimme überwiegend zu
  • 6: Stimme voll zu

special_events

Distribution

old_width = knitr::opts_chunk$get("fig.width")
if (is.null(choices) || dplyr::n_distinct(na.omit(item)) > length(choices)) {
    choices = unique(item)
}
new_width = 1.5 * length(choices)
new_width = ifelse(new_width > 20, 20, new_width)
knitr::opts_chunk$set(fig.width = new_width)
if (dplyr::n_distinct(item) < 20) { 
    dist_plot = ggplot2::ggplot() +
        ggplot2::geom_bar(ggplot2::aes(x = item)) +
        ggplot2::stat_bin(breaks = names(choices)) + 
        ggplot2::ggtitle(item_name, subtitle = item_label) + 
        ggplot2::xlab("Choices")
    
    if (dplyr::n_distinct(item) < 13 && 
            is.numeric(type.convert(names(choices), as.is = T)) && 
            any(names(choices) != unlist(choices))) {
        dist_plot = dist_plot + ggplot2::scale_x_continuous("Choices", breaks = as.numeric(names(choices)), labels = unlist(choices))
    }

    dist_plot
} else {
    cat("More than ", dplyr::n_distinct(item), " unique values, so not shown.")
}
## More than  2012  unique values, so not shown.
knitr::opts_chunk$set(fig.width = old_width)

Summary statistics

pander::pander(skimr::skim_v(item))
type stat level value
character missing .all 28229
character complete .all 2868
character n .all 31097
character min .all 1
character max .all 2077
character empty .all 0
character n_unique .all 2011

Item

item_info$label_parsed = item_info$choices = item_info$choice_list = item_info$study_id = item_info$id = NULL
pander::pander(as.data.frame(t(item_info)))
type type_options name label optional class showif value order
textarea NULL special_events Gab es seit Ihrem letzten Eintrag besondere nennenswerte Ereignisse hinsichtlich Ihres Beziehungslebens? 1 NULL NULL NULL NULL
Choices
if (!is.null(choices) && length(choices) < 20) {
    pander::pander(choices)
}

Missingness report

There were 31053 rows completed, 31097 who entered any information, 0 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame).

Missingness finishers

among those who finished the survey

missingness = missingness_patterns(
    dplyr::select(dplyr::filter(results, !is.na(ended)), -expired, -ended) )
##  index                         col missings
##      1               extra_pair_1b    30646
##      2              special_events    28185
##      3              menstruation_2    26244
##      4              menstruation_3    26244
##      5        sexual_intercourse_4    24518
##      6        sexual_intercourse_3    24517
##      7     communication_partner_2     2127
##      8                extra_pair_3     1094
##      9                extra_pair_4     1094
##     10                extra_pair_5     1094
##     11                extra_pair_6     1094
##     12                extra_pair_7     1094
##     13                extra_pair_8     1094
##     14                extra_pair_9     1094
##     15               extra_pair_10     1094
##     16               extra_pair_11     1094
##     17               extra_pair_12     1094
##     18               extra_pair_13     1094
##     19                 attention_1     1093
##     20                 attention_2     1093
##     21            male_attention_1     1093
##     22                extra_pair_2     1093
##     23                   attention     1093
##     24            mate_retention_6     1092
##     25              NARQ_rivalry_1     1091
##     26              NARQ_rivalry_3     1091
##     27             male_jealousy_1     1091
##     28             male_jealousy_3     1091
##     29       male_mate_retention_1     1091
##     30       male_mate_retention_2     1091
##     31            mate_retention_3     1091
##     32            mate_retention_4     1091
##     33            mate_retention_5     1091
##     34                NARQ_rivalry     1091
##     35               male_jealousy     1091
##     36         male_mate_retention     1091
##     37           NARQ_admiration_1     1090
##     38           NARQ_admiration_2     1090
##     39           NARQ_admiration_3     1090
##     40              NARQ_rivalry_2     1090
##     41                  jealousy_1     1090
##     42             male_jealousy_2     1090
##     43             NARQ_admiration     1090
##     44        desirability_partner     1088
##     45        choice_of_clothing_7     1086
##     46               self_esteem_1     1086
##     47              desirability_1     1086
##     48          choice_of_clothing     1086
##     49        choice_of_clothing_8     1085
##     50        choice_of_clothing_6     1084
##     51        choice_of_clothing_4     1083
##     52        choice_of_clothing_5     1082
##     53        choice_of_clothing_3     1080
##     54        choice_of_clothing_2     1075
##     55        choice_of_clothing_1     1071
##     56        sexual_intercourse_5     1066
##     57                extra_pair_1     1066
##     58              menstruation_1     1066
##     59     communication_partner_1     1065
##     60            mate_retention_1     1065
##     61 relationship_satisfaction_1     1065
##     62            mate_retention_2     1065
##     63        sexual_intercourse_1     1065
##     64        sexual_intercourse_2     1065
pander::pander(missingness)
Pattern Freq Culprit
1_2_3_4_5_6___________________________________________________________________________________________________________________________________________________________________________ 16372
1_2_3_4_______________________________________________________________________________________________________________________________________________________________________________ 5407
1_2_____5_6___________________________________________________________________________________________________________________________________________________________________________ 3581
1_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________ 1742
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64 1065
1_2_3_4_5_6_7_________________________________________________________________________________________________________________________________________________________________________ 726
1_2___________________________________________________________________________________________________________________________________________________________________________________ 523
1_3_4_____________________________________________________________________________________________________________________________________________________________________________ 444
1_______5_6___________________________________________________________________________________________________________________________________________________________________________ 407
2_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________ 215
1_2_____5_6_7_________________________________________________________________________________________________________________________________________________________________________ 119
1_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________ 116
1_____________________________________________________________________________________________________________________________________________________________________________________ 71 extra_pair_1b
25_6________________________________________________________________________________________________________________________________________________________________________ 42
____3_4_5_6___________________________________________________________________________________________________________________________________________________________________________ 37
2_3_4_____________________________________________________________________________________________________________________________________________________________________________ 33
2_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________ 27
1_______5_6_7_________________________________________________________________________________________________________________________________________________________________________ 26
1_2_3_4_____7_________________________________________________________________________________________________________________________________________________________________________ 12
2_________________________________________________________________________________________________________________________________________________________________________________ 10 special_events
____3_4_______________________________________________________________________________________________________________________________________________________________________________ 10
25_6_7______________________________________________________________________________________________________________________________________________________________________ 8
2_______7_________________________________________________________________________________________________________________________________________________________________________ 7
____3_4_5_6_7_________________________________________________________________________________________________________________________________________________________________________ 5
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________ 4
2_3_47______________________________________________________________________________________________________________________________________________________________________ 4
________5_6___________________________________________________________________________________________________________________________________________________________________________ 4
1_2_________7_________________________________________________________________________________________________________________________________________________________________________ 3
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44__________________________________________________________ 2
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_____________________________________________________________ 2
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_________________________________ 2
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_________________________ 2
________5_6_7_________________________________________________________________________________________________________________________________________________________________________ 2
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55___________________________ 1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_55________________________ 1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_________________________________ 1
1_2_3_4_5_6_7__________________________________________________25_26______________________34_______________________________45_______48_______51_______________________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_______________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50________________________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49___________________________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_4446_47_________________________________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_4143_44_45_46_47_48_49_50_51_52_53_54_55_________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_____27_28_29_30_31_32_33_35_36_____________42__________________________________________________________________ 1
1_2_3_4_5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_________________________________________________________________________________________________________________________ 1
1_2_3_4_5_____________________________________________________________________________________________________________________________________________________________________________ 1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58__________________ 1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54______________________________ 1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52____________________________________ 1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24________________________________________________________________________________________________________________________ 1
1_2_3_4_______8_9_10_11_12_13_14_15_16_17_18__________________________________________________________________________________________________________________________________________ 1
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52__________________________________ 1
1_2_____5_6_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50________________________________________ 1
1_3_47______________________________________________________________________________________________________________________________________________________________________ 1
____3_4_____7_________________________________________________________________________________________________________________________________________________________________________ 1
____________7_________________________________________________________________________________________________________________________________________________________________________ 1 communication_partner_2
______________________________________________________________________________________________________________________________________________________________________________________ 1 _

Missingness starters

among those who started the survey

missingness = missingness_patterns(
    dplyr::filter(results, !is.na(modified)) )
##  index                         col missings
##      1                     expired    31097
##      2               extra_pair_1b    30690
##      3              special_events    28229
##      4              menstruation_2    26288
##      5              menstruation_3    26288
##      6        sexual_intercourse_4    24562
##      7        sexual_intercourse_3    24561
##      8     communication_partner_2     2171
##      9                extra_pair_3     1138
##     10                extra_pair_4     1138
##     11                extra_pair_5     1138
##     12                extra_pair_6     1138
##     13                extra_pair_7     1138
##     14                extra_pair_8     1138
##     15                extra_pair_9     1138
##     16               extra_pair_10     1138
##     17               extra_pair_11     1138
##     18               extra_pair_12     1138
##     19               extra_pair_13     1138
##     20                 attention_1     1137
##     21                 attention_2     1137
##     22            male_attention_1     1137
##     23                extra_pair_2     1137
##     24                   attention     1137
##     25            mate_retention_6     1136
##     26              NARQ_rivalry_1     1135
##     27              NARQ_rivalry_3     1135
##     28             male_jealousy_1     1135
##     29             male_jealousy_3     1135
##     30       male_mate_retention_1     1135
##     31       male_mate_retention_2     1135
##     32            mate_retention_3     1135
##     33            mate_retention_4     1135
##     34            mate_retention_5     1135
##     35                NARQ_rivalry     1135
##     36               male_jealousy     1135
##     37         male_mate_retention     1135
##     38           NARQ_admiration_1     1134
##     39           NARQ_admiration_2     1134
##     40           NARQ_admiration_3     1134
##     41              NARQ_rivalry_2     1134
##     42                  jealousy_1     1134
##     43             male_jealousy_2     1134
##     44             NARQ_admiration     1134
##     45        desirability_partner     1132
##     46        choice_of_clothing_7     1130
##     47               self_esteem_1     1130
##     48              desirability_1     1130
##     49          choice_of_clothing     1130
##     50        choice_of_clothing_8     1129
##     51        choice_of_clothing_6     1128
##     52        choice_of_clothing_4     1127
##     53        choice_of_clothing_5     1126
##     54        choice_of_clothing_3     1124
##     55        choice_of_clothing_2     1119
##     56        choice_of_clothing_1     1115
##     57        sexual_intercourse_5     1110
##     58                extra_pair_1     1110
##     59              menstruation_1     1110
##     60     communication_partner_1     1109
##     61            mate_retention_1     1109
##     62 relationship_satisfaction_1     1109
##     63            mate_retention_2     1109
##     64        sexual_intercourse_1     1109
##     65        sexual_intercourse_2     1109
##     66                       ended       44
pander::pander(missingness)
Pattern Freq Culprit
1_2_3_4_5_6_7_______________________________________________________________________________________________________________________________________________________________________________ 16372
1_2_3_4_5___________________________________________________________________________________________________________________________________________________________________________________ 5407
1_2_3_____6_7_______________________________________________________________________________________________________________________________________________________________________________ 3581
1_2_4_5_6_7_____________________________________________________________________________________________________________________________________________________________________________ 1742
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64_65___ 1065
1_2_3_4_5_6_7_8_____________________________________________________________________________________________________________________________________________________________________________ 726
1_2_3_______________________________________________________________________________________________________________________________________________________________________________________ 523
1_2_4_5_________________________________________________________________________________________________________________________________________________________________________________ 444
1_2_______6_7_______________________________________________________________________________________________________________________________________________________________________________ 407
1_3_4_5_6_7_____________________________________________________________________________________________________________________________________________________________________________ 215
1_2_3_____6_7_8_____________________________________________________________________________________________________________________________________________________________________________ 119
1_2_4_5_6_7_8___________________________________________________________________________________________________________________________________________________________________________ 116
1_2_________________________________________________________________________________________________________________________________________________________________________________________ 71
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_60_61_62_63_64_65_66 44
1_36_7____________________________________________________________________________________________________________________________________________________________________________ 42
1_____4_5_6_7_______________________________________________________________________________________________________________________________________________________________________________ 37
1_3_4_5_________________________________________________________________________________________________________________________________________________________________________________ 33
1_3_4_5_6_7_8___________________________________________________________________________________________________________________________________________________________________________ 27
1_2_______6_7_8_____________________________________________________________________________________________________________________________________________________________________________ 26
1_2_3_4_5_____8_____________________________________________________________________________________________________________________________________________________________________________ 12
1_3_____________________________________________________________________________________________________________________________________________________________________________________ 10
1_____4_5___________________________________________________________________________________________________________________________________________________________________________________ 10
1_36_7_8__________________________________________________________________________________________________________________________________________________________________________ 8
1_3_______8_____________________________________________________________________________________________________________________________________________________________________________ 7
1_____4_5_6_7_8_____________________________________________________________________________________________________________________________________________________________________________ 5
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_______________________________ 4
1_3_4_58__________________________________________________________________________________________________________________________________________________________________________ 4
1_________6_7_______________________________________________________________________________________________________________________________________________________________________________ 4
1_2_3_________8_____________________________________________________________________________________________________________________________________________________________________________ 3
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_____________________________________________________________ 2
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44________________________________________________________________ 2
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________________ 2
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56____________________________ 2
1_________6_7_8_____________________________________________________________________________________________________________________________________________________________________________ 2
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56______________________________ 1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_56___________________________ 1
1_2_3_4_5_6_7_8_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54____________________________________ 1
1_2_3_4_5_6_7_8___________________________________________________26_27______________________35_______________________________46_______49_______52__________________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54__________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51___________________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50______________________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_4547_48____________________________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_4244_45_46_47_48_49_50_51_52_53_54_55_56____________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_____28_29_30_31_32_33_34_36_37_____________43_____________________________________________________________________ 1
1_2_3_4_5_6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24____________________________________________________________________________________________________________________________ 1
1_2_3_4_5_6_________________________________________________________________________________________________________________________________________________________________________________ 1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_56_57_58_59_____________________ 1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_54_55_________________________________ 1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_______________________________________ 1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25___________________________________________________________________________________________________________________________ 1
1_2_3_4_5_______9_10_11_12_13_14_15_16_17_18_19_____________________________________________________________________________________________________________________________________________ 1
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51_52_53_____________________________________ 1
1_2_3_____6_7_9_10_11_12_13_14_15_16_17_18_19_20_21_22_23_24_25_26_27_28_29_30_31_32_33_34_35_36_37_38_39_40_41_42_43_44_45_46_47_48_49_50_51___________________________________________ 1
1_2_4_58__________________________________________________________________________________________________________________________________________________________________________ 1
1_____4_5_____8_____________________________________________________________________________________________________________________________________________________________________________ 1
1_____________8_____________________________________________________________________________________________________________________________________________________________________________ 1
1___________________________________________________________________________________________________________________________________________________________________________________________ 1 expired

Items

DT::datatable(dplyr::select(as.data.frame(diary_items), -choice_list, -id, -study_id, -index), rownames = FALSE, filter = "top", extensions = 'Buttons', options = list(
    dom = 'Bfrtip',
    buttons = c('copy', 'csv', 'excel', 'pdf', 'print'),
    pageLength = 200
  ))